2006Unpublished venueRequires access

Solving the Traveling Salesman Problem through Genetic Algorithms with Changing Crossover Operators

Ryouei Takahashi

Open publisher page 16 citations

Abstract

In order to solve the traveling salesman problem (TSP) through genetic algorithms (GAs), a method of changing crossover operators (CXO), which can flexibly substitute the current crossover operator for another suitable crossover operator at any time, is proposed. This paper reports experimental validation of CXO through C software by using data of 200 cities.

About this research paper

What this paper is about

In order to solve the traveling salesman problem (TSP) through genetic algorithms (GAs), a method of changing crossover operators (CXO), which can flexibly substitute the current crossover operator for another suitable crossover operator at any time, is proposed. This paper reports experimental validation of CXO through C software by using data of 200 cities.

Why it matters

OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In order to solve the traveling salesman problem (TSP) through genetic algorithms (GAs), a method of changing crossover operators (CXO), which can flexibly substitute the current crossover operator for another suitable crossover operator at any time, is proposed. This paper reports experimental validation of CXO through C software by using data of 200 cities.

Key concepts: Crossover, Travelling salesman problem, Operator (biology), Genetic algorithm, Computer science, Mathematical optimization, Bottleneck traveling salesman problem, 2-opt

Related papers

Back to paper searchBrowse research topicsOriginal source
Solving the Traveling Salesman Problem through Genetic Algorithms with Changing Crossover Operators — Research Paper | ScholarLens